Pseudorandom Maximum Length Signal Design with Bias Compensation Least Squares Estimation for System Identification

2007 ◽  
Author(s):  
Mathias Fui Lin Foo ◽  
Ai Hui Tan ◽  
Kartik Prasad Basu
Keyword(s):  
System Identification ◽  
Least Squares ◽  
Least Squares Estimation ◽  
Maximum Length ◽  
Signal Design ◽  
Bias Compensation

scholarly journals Duality of variable fractional order difference operators and its application in identification

2014 ◽  
Vol 62 (4) ◽  
pp. 809-815 ◽  
Author(s):  
D. Sierociuk ◽  
M. Twardy
Keyword(s):  
System Identification ◽  
Least Squares ◽  
Fractional Order ◽  
Least Squares Estimation ◽  
Difference Operators ◽  
Variable Order ◽  
Fractional Systems ◽  
Order Difference

Abstract The paper presents a number of definitions of variable order difference and discusses duality among some of them. The duality is used to improve the performance of the least squares estimation when applied to variable order difference fractional systems. It turns out, that by appropriate exploitation of duality one can reduce the estimator variance when system identification is carried out.

The Estimation of Blood Platelet Survival

1972 ◽  
Vol 28 (03) ◽  
pp. 447-456 ◽  
Author(s):  
E. A Murphy ◽  
M. E Francis ◽  
J. F Mustard
Keyword(s):  
Standard Deviation ◽  
Least Squares ◽  
Experimental Error ◽  
Blood Platelet ◽  
Least Squares Estimation ◽  
Systematic Relationship ◽  
Platelet Survival ◽  
The Mean ◽  
Normally Distributed

SummaryThe characteristics of experimental error in measurement of platelet radioactivity have been explored by blind replicate determinations on specimens taken on several days on each of three Walker hounds.Analysis suggests that it is not unreasonable to suppose that error for each sample is normally distributed ; and while there is evidence that the variance is heterogeneous, no systematic relationship has been discovered between the mean and the standard deviation of the determinations on individual samples. Thus, since it would be impracticable for investigators to do replicate determinations as a routine, no improvement over simple unweighted least squares estimation on untransformed data suggests itself.

Least Squares Estimation in Uncertain Differential Equations

2020 ◽  
Vol 28 (10) ◽  
pp. 2651-2655 ◽  
Author(s):  
Yuhong Sheng ◽  
Kai Yao ◽  
Xiaowei Chen
Keyword(s):  
Differential Equations ◽  
Least Squares ◽  
Least Squares Estimation
Sign in / Sign up

Export Citation Format

Share Document